Quantitative Statistical Methods

Scholar Year: 2023/2024 - 1S

Courses

Head Teacher Responsability Sandra Cristina Dias Nunes Head

Weekly workload Hours/week T TP P PL L TC E OT OT/PL TPL O S Type of classes 2 Lectures Type Teacher Classes Hours Theoretical-practical Totals 1 2,00 Sandra Nunes   2,00

Teaching language

Portuguese

Intended learning outcomes (Knowledges, skills and competencies to be developed by the students)

At a time when the development of computer science is advancing rapidly, the analysis of statistical data has assumed a key role in the field of modeling, prediction and interpretation of phenomena in areas such economics, finances and management.
In this curricular unit our aim is to present the major statistical methods used for analyzing data in social and business sciences; modeling and forecasting time series techniques; correlation analysis; simple and multiple linear regression; principal component analysis, factor analysis, cluster analysis and discriminant analysis. All these statistical tools will allow students to interpret, formalize and solve relevant problems involving quantitative data analysis. This course will show our students that the statistical theoretical foundations are essential but our classes will be eminently practical using statistical software such as SPSS and Eviews to solve practical problems using, whenever possible, real data.

Syllabus

I - Basic statistical concepts and introduction to the software SPSS

II - Parametric and Non Parametric Tests
Applications with SPSS

III- Correlation Analysis
Applications with SPSS

IV - Linear Regression
Applications with SPSS

V - Exploratory Analysis of Multivariate Data
Applications with SPSS

VI - Prediction Methods
Applications with SPSS

Software

SPSS

Demonstration of the syllabus coherence with the UC intended learning outcomes

The Quantitative Statistical Methods as a course which belongs to the Mathematics scientific area, is a subject essential in social and economic sciences because it allows working with large samples using the appropriate software. The contents are built to allow the acquisition of the theoretical background needed in several areas of business and management and the consequent practical application of them. The program begins with a brief review of basic statistical concepts arming students with the basic statistical tools essential to the learning of other content. At the same time an introduction to the appropriate software is made. Then the most important concepts in several areas of multivariate statistical analysis and forecasting methods are introduced. The acquisition of new knowledge in parallel with the use of statistical software allows students to achieve the defined objectives: to formalize, to interpret and to solve real problems with real data.

Teaching methodologies

The teaching methods applied are defined according to the type of classes and the type of objective. Classes are divided into theoretical and laboratory.
Theoretical part: Methodology Expository, by making use of participatory methodology;
Laboratory part: Participatory Methodology through exercises using appropriate software;
Student attendance: Clarification of doubts; support for carrying out students work.

Final Evaluation (first season):


• Final Test (individual) (T);
• Group Work (TG) .

The group work will have to fulfill a schedule of activities defined by the teacher that will include a written report and an oral presentation

Final Grade= 0,5 x T + 0,5 x TG


The minimum score required either to the group work or to the individual test is 10.

If the final grade is less than 10, the student must perform the appeal season. Final Evaluation (second season): it is for students who did not attend or who did not obtain approval in the first one. The evaluation system is the same.

Demonstration of the teaching methodologies coherence with the curricular unit's intended learning outcomes

The selection of methods to be used is based on defined objectives.
In the curricular unit of Quantitative Statistical Methods although lectures are classified as theoretical - practical in order to meet the objectives each class is divided into distinct parts: theoretical and laboratory. The theoretical part is mainly based on expository methods but also supported by pratical examples and, whenever possible, encouraging students participation. This method used in the theoretical classes with the invitation to participate, helps to clarify concepts, helps to reflect on the contents and help students in structuring, discrimination and integration of cognitive elements, developing the critical thinking and the mathematical reasoning.
The laboratory part is focused on the idea of “know-how”, supported on practical activities of solving exercises and problems through the application of concepts provided in the theoretical classes using the appropriate software. These activities should be performed mainly by the students; the teacher should only facilitate.
Theoretical classes are followed by sequential practical laboratorial classes with exercises in order to apply all the knowledge learned in previous theoretical classes. These sequential exercises help and reinforce the knowledge and to understand that the theoretical knowledge is essential to a good practical application of it.

Assement and Attendance registers

Bibliography

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